Given the increased popularity of smartphones, malware targeting mobile platforms have become a real concern. A lot of commercial anti-malware products have been developed in order to defend users against this types of threats. These solutions have become more and more sophisticated in detecting known malware, but are they really resilient against obfuscation techniques? In order to evaluate the effectiveness of different anti-malware products we propose AAMO, a fully automated modular framework capable of applying some common and mobile-tailored obfuscation techniques to a large-scale dataset of malware samples. AAMO is capable of combining multiple obfuscation techniques in order to achieve complex obfuscation, it also provides a fast and easy way to apply them to any Android application. Exploiting the obfuscation pipeline provided by AAMO is also possible to make an educated guess on witch signature-matching technique is used by different anti-malware products. None of the tools we have tested is fully resilient against obfuscation techniques, and we show that, when applied together, even simple obfuscation techniques can annihilate the detection capabilities of any tested product, down to zero percent. Given the knowledge acquired we propose a set of remediations for improving the robustness of detection techniques.